The SEM for outdoor walking.

Note: The format of factor loadings and covariances: standardized estimation (standard error) significance level; the format of path coefficients: unstandardized estimation (standard error) significance level. * p p p < .001. The green color indicates a positive relationship while red color indicates a negative relationship.</p

Initial measurement model for the environmental factors.

Note: A: higher scores indicate higher density; B: higher scores indicate higher level of land use mix diversity; C: higher scores indicate higher level of land use mix access; D: higher scores indicate more street connectivity; E: higher scores indicate more infrastructure and safer neighborhood; F: higher scores indicate more aesthetically appealing neighborhood; G: higher scores indicate more traffic hazards; H: higher scores indicate higher crime rate and feeling of unsafe to walk in the neighborhood; I: higher scores indicate that parking is more difficult in local shopping areas; J: higher scores indicate lack of cul-de-sacs; K: higher scores indicate that the streets in the neighborhood is more hilly; L: higher scores indicate more physical barriers to walking in the neighborhood; N: higher scores indicate more social interactions while walking in the neighborhood. (TIF)</p

Modified measurement model for the environmental factors.

Note: The format of factor loadings and covariances: standardized estimation (standard error) significance level. * p < .05; **.01 < p < .05; *** p < .001. The green color indicates a positive relationship while red indicates a negative relationship. A: higher scores indicate higher density; E: higher scores indicate more infrastructure and safer neighborhood; F: higher scores indicate more aesthetically appealing neighborhood; G: higher scores indicate more traffic hazards; H: higher scores indicate higher crime rate and feeling of unsafe to walk in the neighborhood; I: higher scores indicate that parking is more difficult in local shopping areas; K: higher scores indicate that the streets in the neighborhood is more hilly; L: higher scores indicate more physical barriers to walking in the neighborhood; N: higher scores indicate more social interactions while walking in the neighborhood.</p

R code.

ObjectiveTo estimate the relationships between individual and environmental variables and outdoor walking (OW) in older adults with OW limitations through verifying a conceptual model.MethodsBaseline data from 205 older adults participating in a randomized trial of a park-based OW program were analyzed using structural equation modeling. We evaluated a three latent factor model: OW (accelerometry and self-report); individual factors (balance; leg strength; walking self-confidence, speed and endurance; mental health; education; income; car access); and environmental factors (neighbourhood walkability components).ResultsMean age was 75 years; 73% were women. Individual factors was significantly associated with OW (β = 0.39, p p ConclusionsBetter walking capacity and more confidence in the ability to walk outdoors are associated with higher OW in older adults. Better neighbourhood walkability is indirectly associated with more OW. The conceptual model demonstrates an individual and environment association; if the capacity of the individual is increased (potentially through walking interventions), they may be able to better navigate environmental challenges.</div

Participant characteristics (n = 205).

ObjectiveTo estimate the relationships between individual and environmental variables and outdoor walking (OW) in older adults with OW limitations through verifying a conceptual model.MethodsBaseline data from 205 older adults participating in a randomized trial of a park-based OW program were analyzed using structural equation modeling. We evaluated a three latent factor model: OW (accelerometry and self-report); individual factors (balance; leg strength; walking self-confidence, speed and endurance; mental health; education; income; car access); and environmental factors (neighbourhood walkability components).ResultsMean age was 75 years; 73% were women. Individual factors was significantly associated with OW (β = 0.39, p p ConclusionsBetter walking capacity and more confidence in the ability to walk outdoors are associated with higher OW in older adults. Better neighbourhood walkability is indirectly associated with more OW. The conceptual model demonstrates an individual and environment association; if the capacity of the individual is increased (potentially through walking interventions), they may be able to better navigate environmental challenges.</div

Modified measurement model for the individual factors.

Note: The format of factor loadings and covariances: standardized estimation (standard error) significance level. * p < .05; **.01 < p < .05; *** p < .001. The green color indicates a positive relationship while red indicates a negative relationship.</p

The adapted SEM based on the GO-OUT conceptual framework for outdoor walking using device-based measurement.

The adapted SEM based on the GO-OUT conceptual framework for outdoor walking using device-based measurement.</p

Initial measurement model for the individual factors.

Initial measurement model for the individual factors.</p

Structural equation model using data excluding participants who had the 6-minute test with a 10-meter walkway instead of the 30-meter walkway in the protocol.

Note: The format of factor loadings and covariances: standardized estimation (standard error) significance level; the format of path coefficients: unstandardized estimation (standard error) significance level. * p (TIF)</p

Correlation coefficient matrix of all variables.

ObjectiveTo estimate the relationships between individual and environmental variables and outdoor walking (OW) in older adults with OW limitations through verifying a conceptual model.MethodsBaseline data from 205 older adults participating in a randomized trial of a park-based OW program were analyzed using structural equation modeling. We evaluated a three latent factor model: OW (accelerometry and self-report); individual factors (balance; leg strength; walking self-confidence, speed and endurance; mental health; education; income; car access); and environmental factors (neighbourhood walkability components).ResultsMean age was 75 years; 73% were women. Individual factors was significantly associated with OW (β = 0.39, p p ConclusionsBetter walking capacity and more confidence in the ability to walk outdoors are associated with higher OW in older adults. Better neighbourhood walkability is indirectly associated with more OW. The conceptual model demonstrates an individual and environment association; if the capacity of the individual is increased (potentially through walking interventions), they may be able to better navigate environmental challenges.</div